71–80 of 90 posts
Surprised to see no one here is worried about privacy. Z.ai's privacy policy pretty much allows them to store and use prompts/code in a perpetual, irrevocable, worldwide, sublicensable license to use and train their models.
I've been using GLM 4.5 and GLM 4.5 Air for a while now. The Air model is light enough to run on a macbook pro and is useful for Cline. I can run the full GLM model on my Mac Studio, but the TPS is so slow that it's only useful for chatting. So I hooked up with openrouter to try but didn't have the same success. Any of the open weight models I try with open router give sub standard results. I get better results from…
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I called it "chinnese chatpcha", back then chinnese chaptcha is so much harder than western counterpart but now gchaptcha spam me with 5 different image if I missing a tiles for crossroad, so chinnese chaptcha is much better in my opinion also there is variant that match the image based on shadow and different order of shape its much better in my opinion because its use much more interactivity, solving western chaptc…
I assume both of the approaches are useless at actually stopping bots
Why trying CC why not using alternatives like Opencode or Goose that are open and made for this purpose instead of trying to use a tool tailored by Anthropic for Anthropic models?
CC system prompt is tuned for Sonnet 4/Opus Why trying CC why not using alternatives like Opencode or Goose that are open and made for this purpose instead of trying to use a tool tailored by Anthropic for Anthropic models?
CC system prompt is tuned for Sonnet 4/Opus Why trying CC why not using alternatives like Opencode or Goose that are open and made for this purpose instead of trying to use a tool tailored by Anthropic for Anthropic models?
* This is an excellent alternative to Sonnet - which was my daily driver. I'm glad I tried GLM 4.5. You won't find any difference.
* My context usage per session was about 50% with Sonnet earlier, but it fills up fast with GLM, and I hit 80-90% often. Could be the lower context size that is hurting.
* Sonnet used to be very painful to work with as the context size goes beyond 80% (hence my habit of shorter conversations). GLM holds itself well even until the last bit of remaining context. Does not deviate from the assigned task.
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you can use any model with Claude code thanks to https://github.com/musistudio/claude-code-router but in my testing other models do not work well, looks like prompts are either very optimized for Claude, or other models are just not great yet with such agentic environment I was especially disappointed with grok code. it is very fast as advertised but in generating spaces and new lines in function calling until it hit…
> but in my testing other models do not work well, looks like prompts are either very optimized for Claude, or other models are just not great yet with such agentic environment I think there are multiple things going on. First, models are either trained with tool calling in mind or not, the ones that don't, won't work well as agents. Secondly, each companies models are trained with the agent software in mind, and the…
Claude code router is a good first step. But you also need to MITM CC while it’s running and collect the back and forth for a while. I would do it if I had more free time, surprised someone smart hasn’t already tried.
The graphs that some of these companies make are brutal: https://docs.z.ai/guides/llm/glm-4.5#higher-parameter-effici... "So, we only know the Y-axis for some models in the scatter plot. Let's make up an X-axis value on the bad side of the graph and include the data points anyway." Visually disingenuous!
Which x axis was made up? You mean showing barplots in descending order of scores?
“Model Parameters (B)” has an “Unknown” column to the right of 1000, implying those models are 1200B or more parameters, which is just not the case.
It renders the comparison useless, they can really only claim best efficiency against other open weight models.